Feature linking and pattern separation are shown to be performed as simultaneous processes by a highly connected auto-associative network of spiking neurons (spike response model). In principle, many (e.g., with nine) patterns can be separated, but with a biological set of parameters the number is limited to four. The patterns have been learned by an asymmetric hebbian rule that can handle a low activity which may vary from pattern to pattern (in a range between 4% and 7%). Spikes are generated by a threshold process and--with some delay--transmitted to postsynaptic neurons. There they evoke an excitatory or inhibitory postsynaptic potential (EPSP or IPSP). Spike emission is followed by an absolute refractory period (1 ms) and activates an inhibitory delay loop that prevents continuous firing. Three different network topologies are discussed, i.e., a structureless fully connected system, a network composed of two 'hemispheres', and finally a hierarchical network with four subsystems that represent different 'functions' and interact via feedforward and feedback connections. Functional feedback turns out to be essential for context-sensitive binding. The coherence between the two hemispheres is dependent on the interhemispheric delays. If these are on average too large, the two hemispheres oscillate coherently by themselves but phase-shifted by half a period with respect to each other.

Feature linking and pattern separation are shown to be performed as simultaneous processes by a highly connected auto-associative network of spiking neurons (spike response model). In principle, many (e.g., with nine) patterns can be separated, but with a biological set of parameters the number is limited to four. The patterns have been learned by an asymmetric hebbian rule that can handle a low activity which may vary from pattern to pattern (in a range between 4% and 7%). Spikes are generated by a threshold process and--with some delay--transmitted to postsynaptic neurons. There they evoke an excitatory or inhibitory postsynaptic potential (EPSP or IPSP). Spike emission is followed by an absolute refractory period (1 ms) and activates an inhibitory delay loop that prevents continuous firing. Three different network topologies are discussed, i.e., a structureless fully connected system, a network composed of two 'hemispheres', and finally a hierarchical network with four subsystems that represent different 'functions' and interact via feedforward and feedback connections. Functional feedback turns out to be essential for context-sensitive binding. The coherence between the two hemispheres is dependent on the interhemispheric delays. If these are on average too large, the two hemispheres oscillate coherently by themselves but phase-shifted by half a period with respect to each other.

To achieve the Paris Agreement’s long-term temperature goal, current energy systems must be transformed. Australia represents an interesting case for energy system transformation modeling: with a power system dominated by fossil fuels and, specifically, with a heavy coal component, there is at the same time a vast potential for expansion and use of renewables. We used the multi-sectoral Australian Energy Modeling System (AUSeMOSYS) to perform an integrated analysis of implications for the electricity, transport, and selected industry sectors to the mid-century. The state-level resolution allows representation of regional discrepancies in renewable supply and the quantification of inter-regional grid extensions necessary for the physical integration of variable renewables. We investigated the impacts of different CO2 budgets and selected key factors on energy system transformation. Results indicate that coal-fired generation has to be phased out completely by 2030 and a fully renewable electricity supply achieved in the 2030s according to the cost-optimal pathway implied by the 1.5 °C Paris Agreement-compatible carbon budget. Wind and solar PV can play a dominant role in decarbonizing Australia’s energy system with continuous growth of demand due to the strong electrification of linked energy sectors.

Abstract. A model of vertical signal flow across a layered cortical structure is presented and analyzed. Neurons communicate through spikes, which evoke an excitatory or inhibitory postsynaptic potential (spike response model). The layers incorporate two anatomical features -dendritic and axonal arborization patterns and distance-dependent time delays. The vertical signal flow through the network is discussed for various stimulus conditions using two different, but typical, axonal arborization patterns. We find stationary as well as oscillatory response, but the oscillatory response may be restricted to a single layer. Confronted with conflicting stimuli the network separates the patterns through phase-shifted oscillations. We also discuss two hypothetical animals, to be called "cat" and "mouse." These have different axonal arborizations, which give rise to a different oscillatory response (if any) of the various layers.